What does a $100 million public health data revolution look like?
Summary
TLDRThe speaker discusses the importance of real-time health data in managing complex systems, exemplified by Rio de Janeiro's smart city initiative. They introduce a global health data tool, created by 500 experts over five years, which provides insights into disease patterns by age, sex, and locality for 187 countries. The tool reveals a shift from child mortality to non-communicable diseases in aging populations, with significant variations across countries. It also identifies leading risk factors like diet and smoking in the U.S., emphasizing the tool's potential to transform population health by learning from global patterns.
Takeaways
- 🚗 The speaker uses the metaphor of getting to a destination, emphasizing the importance of clear information, roadmaps, and anticipating obstacles for success.
- 🏙️ The evolution of smart cities like Rio de Janeiro, which gather real-time data to manage complex systems, is highlighted as a model for efficient responses in large cities.
- 🌍 Over 500 experts from 50 countries have compiled global health data covering more than 1,000 clinical outcomes for 187 countries over two decades, providing invaluable insights.
- 📊 From 1990 to 2010, the world saw significant progress in reducing child mortality and shifting the burden of disease to older populations, especially heart disease and cancer.
- 👶 While deaths have decreased, premature mortality in children remains a large issue, with neonatal causes, diarrhea, pneumonia, and malaria still prominent in many areas.
- 🧠 Mental and musculoskeletal disorders, along with hearing and vision loss, are significant contributors to global health problems, even though they do not cause direct mortality.
- 🌍 The burden of disease varies greatly by region, with West Africa facing primarily communicable diseases and China having transitioned to non-communicable diseases like heart disease and cancer.
- 📉 China has made remarkable progress in reducing communicable diseases by 80% since 1990, although it faces rising challenges from ischemic heart disease, offering lessons for other nations.
- 🍽️ Risk factors like diet, smoking, obesity, and high blood pressure dominate health loss in the U.S., highlighting lifestyle changes as critical to improving overall health.
- 🔬 The project combines data, science, and visualization tools to give everyone—not just specialists—access to a deep understanding of global health patterns, helping to improve public health at the community level.
Q & A
What is the key message of the speaker's introduction regarding reaching a destination?
-The speaker emphasizes the importance of knowing how to reach a destination, including factors such as means of transport, clarity of the destination, potential obstacles, and tools to navigate the route. This analogy introduces the complexity of managing systems, particularly in health and first-response contexts.
What is the role of smart cities in first-response management, as explained in the transcript?
-Smart cities, like Rio de Janeiro, gather real-time data to manage complex systems such as first-response services. This allows the city to handle emerging problems more effectively and ensure timely responses to emergencies.
What significant health data collection project does the speaker mention?
-The speaker mentions a project involving 500 people from 50 countries who, over five years, compiled health data on more than 1,000 clinical outcomes for 187 countries. This dataset spans two decades and provides insights into global health patterns, including progress made in various health conditions.
What are the key insights from global child mortality trends between 1990 and 2010?
-Between 1990 and 2010, global child mortality decreased significantly from 12 million to 7 million deaths. There was also a shift in the age distribution of deaths, with more people living to age 80 or older, showing global health improvements over time.
Why does the speaker emphasize premature mortality when discussing global health?
-The speaker highlights premature mortality to emphasize that not all deaths are equal in terms of life years lost. For example, a death at age five results in more years of lost potential life compared to a death at age 95. This concept helps better understand the broader impact of early deaths.
What are some of the major health issues affecting young adults globally, according to the transcript?
-Major health issues affecting young adults include HIV/AIDS, tuberculosis, road accidents, homicide, and suicide. These conditions contribute significantly to premature mortality in this age group.
What does the speaker mean by 'what ails you globally isn't actually what kills you'?
-The speaker is referring to the distinction between conditions that cause death and those that cause non-fatal health problems. While conditions like heart disease and cancer may be leading causes of death, mental disorders, musculoskeletal disorders, and sensory impairments (e.g., vision and hearing loss) are major contributors to global health problems that don't necessarily result in death.
How has the burden of disease in China shifted between 1990 and 2010?
-In 1990, 25% of the disease burden in China was from communicable diseases. By 2010, this figure dropped significantly, and non-communicable diseases such as heart disease, cancer, and mental disorders now account for 80% of the disease burden. This reflects China's success in reducing infectious diseases but highlights new challenges with non-communicable diseases.
What are some of the leading risk factors for health loss in the United States?
-In the United States, the leading risk factors for health loss are poor diet, smoking, obesity, high blood pressure, high blood sugar, physical inactivity, and alcohol use. These factors contribute significantly to the country's overall health burden.
What are the three main takeaways the speaker wants the audience to remember about global health data and tools?
-The speaker's three main takeaways are: (1) The tools allow us to ask new and insightful questions about global health; (2) We can learn from both successes and failures across the world to improve health outcomes; and (3) These tools empower everyone, not just specialists, to engage in improving health globally.
Outlines
🚑 The Role of Data in First Response and Global Health
The speaker opens by asking the audience to consider the importance of information in reaching a destination, particularly in emergency responses within large cities. He introduces the concept of smart cities, such as Rio de Janeiro, where real-time data is used to manage emergencies. The discussion then shifts to a global scale, focusing on health systems and how data collection over the last two decades—covering thousands of clinical outcomes for 187 countries—has provided insights into disease patterns. The speaker highlights the availability of this data online and emphasizes the progress in reducing child mortality between 1990 and 2010.
📊 Premature Mortality and Health Complexity
The speaker dives deeper into the issue of premature mortality, explaining how years of life lost is a better measure than just counting deaths. He illustrates the burden of diseases like diarrhea, pneumonia, and malaria, particularly in children, but also brings attention to young adult mortality from causes like HIV and road accidents. He emphasizes that health is more than avoiding death, mentioning that diseases such as mental disorders, musculoskeletal issues, and vision loss contribute significantly to the global health burden. The discussion moves toward country-specific health challenges, showing how non-communicable diseases have become more prevalent in countries like China.
📉 Tracking Changes in Disease Burden Over Time
The speaker introduces a ranked list comparing health loss in China from 1990 to 2010, showing the dramatic reduction in communicable diseases like tuberculosis and pneumonia, alongside a rise in ischemic heart disease. This comparison underscores the significant epidemiological shift in China over two decades. The speaker stresses that these trends offer lessons for both China and other developing nations on managing health transitions and emphasizes the value of understanding specific diseases for targeted health interventions.
🛡️ The Impact of Risk Factors on Health
The speaker shifts to the topic of risk factors, presenting the U.S. as a case study. He lists diet, smoking, obesity, high blood pressure, and physical inactivity as the leading contributors to health loss. The speaker reiterates the importance of using data to explore risk factors and health outcomes in different populations, encouraging the audience to explore these tools themselves. He introduces the idea that these risk factors can be modified both individually and at the community level to improve public health outcomes.
🌍 The Power of Data in Global Health Improvement
The speaker recounts a personal story about his parents' work in healthcare, which inspired his career in understanding global health patterns. He reflects on the challenges of synthesizing health data from various sources and regions, emphasizing the need for robust science to account for biases and inconsistencies in data collection. He celebrates the emergence of data scientists and advanced visualization tools that now make this complex data accessible to everyone, enabling better health interventions worldwide.
🏥 Lessons from Life Expectancy Disparities
The speaker concludes with a powerful illustration of health disparities within the U.S., showing that life expectancy can vary by up to 12 years depending on the county. He uses this disparity to emphasize the potential for health improvement by studying successful health interventions in different communities and regions. He advocates for a collective effort to use data to ask new questions, learn from global successes and failures, and empower everyone to contribute to better health outcomes, not just specialists.
Mindmap
Keywords
💡Smart Cities
💡Global Health Data
💡Premature Mortality
💡Non-communicable Diseases (NCDs)
💡Communicable Diseases
💡Burden of Disease
💡Risk Factors
💡Health Visualization
💡Epidemiological Shift
💡Health Disparities
Highlights
Smart cities like Rio de Janeiro are using real-time data to manage complex systems, first responders, and urban challenges.
A global health database has been compiled by 500 people from 50 countries over five years, covering over a thousand clinical outcomes for 187 countries.
The data provides insights into patterns of disease by age, sex, and locality, highlighting areas making progress and those that are lagging behind.
Child mortality worldwide has decreased from 12 million deaths in 1990 to 7 million in 2010, with a shift in deaths to older populations.
Premature mortality is a key focus, showing significant loss of years of life in children due to preventable causes like diarrhea, pneumonia, and neonatal issues.
In young adults, diseases like HIV, tuberculosis, road traffic accidents, and mental health disorders are major causes of premature death.
Global health is not just about mortality but also the burden of disease, with mental disorders, musculoskeletal issues, and sensory impairments like hearing and vision loss contributing significantly.
Health outcomes vary greatly by country, with countries like China showing a shift from communicable to non-communicable diseases over the past two decades.
China has reduced its communicable disease burden by 80% since 1990, while ischemic heart disease has risen by 50%.
The tool developed allows users to visualize health loss from both diseases and risk factors, highlighting dietary risks, smoking, obesity, and high blood pressure as major contributors in the U.S.
Data collection from various sources, including handwritten records, is crucial to understanding global health patterns, despite biases and inconsistencies in medical reporting.
A new generation of data scientists is using advanced techniques to turn raw health data into actionable insights.
Visualization tools make complex health data accessible, helping users engage with information and ask new questions about global health trends.
The tool highlights disparities within countries, such as U.S. counties where life expectancy for women is equivalent to that in Libya.
By learning from both successful and struggling regions, communities can 'leapfrog' in improving health outcomes globally, benefiting from shared knowledge.
Transcripts
so I want to start by getting you to
think about a question if you want to
get to a destination what's going to
help you to get there now some of you
are going to be thinking about a means
of transport clarity of where you want
to go maybe a road map and you want to
know about obstacles along the way
traffic jams weather road closures road
construction now imagine for a moment
that you're in charge of first
responders in a large crowded city and
those that information is even more
important because it really matters
getting the response the people in need
and so we're seeing the evolution of
smart cities this is Rio de Janeiro
where they've real-time gather
information so that they're able to
manage a complex system manage
first-response manage problems that
emerge in a number of systems in that
city what if we had that information for
even more complex things like the
world's health systems now the good news
which we already heard a little bit
about is that that information is
actually now being put together so 500
people from 50 countries over five years
have put together all the world's data
on an enormous number of conditions more
than a thousand different clinical
outcomes by age by sex for 187 countries
over the last two decades giving us
insights into where the pattern of
disease is by age by sex by locality
who's making progress who's not and as
we heard that information is not just in
a commanding control center like we saw
for Rio de Janeiro but that information
is online you can go get it now and
hopefully you'll go get it after this
presentation so there's a billion
results in this accumulation of the
world's
health data and I'm going to give you a
sort of world quick tour of some of the
insights you can get from these tools so
let's start with something very simple
and that is death death by age so this
is one of our live tools it shows in
this case death for the world in 1990
and there are four age groups on the far
left for children and there are all the
other age groups up to eighty plus and
you can see 21 groups of causes yellow
sticks out that's diarrhea pneumonia a
big killer of children the dark blue is
heart disease the lighter blue is cancer
and from 1990 to 2010 we had a lot of
progress in the world so let's see that
again go back to 1990 go forward to 2010
and what you see is that we've reduced
child mortality in the world from about
12 million deaths to about 7 million
deaths and we've had a big shift to
death over age 80 progress but deaths
don't tell the whole story in fact if
you die at age five you've lost most of
your lifespan if you die at age 95
you've lost much less and so we have to
help get the big picture a construct
called premature mortality and now I'm
showing you the number of years lost in
the world by caused by age and you can
see the agenda of tackling premature
death and children is still really large
the big bars in the far left neonatal
causes diarrhea pneumonia and malaria
still important but you can also see in
young adults the dark yellow
that's HIV and tuberculosis you can see
the dark purple those are road transport
accidents and things like homicide and
suicide show up is that salmon color
there's a big agenda around young adult
mortality as well but health is a lot
more than simply avoiding death that's
why we're so interested in wellness
that's why in this study we look at over
a thousand different outcomes and we put
it all together and count up the number
of years lost due to different diseases
taking into account how severe they are
and what's important here is the
dollars on this diagram are different
than the one I just showed you the ones
that leap out are the light green which
are mental disorders and substance abuse
the light purple which are the
musculoskeletal disorders and the darker
purple are things like vision loss that
we just heard about in hearing loss and
congenital anomalies what ails you
globally isn't actually what kills you
and so when you put those two together
you get a global view of all the
complexity about health premature
mortality and children from infectious
diseases cancer and heart disease road
traffic accidents HIV mental disorders
but of course the world is not one
homogeneous whole and part of the power
of this tool is that you can now explore
country by country what are the big
causes and how they're changing so this
view on the top is a square pie chart
just like a pie chart the size of each
box is proportionate to the problem and
the non communicable diseases heart
disease cancer musculoskeletal disorders
mental disorders are in blue the
communicable causes in red and injuries
are in green and on the map on the
bottom is the fraction of health loss in
each country due to the communicable
causes in West Africa in the country of
leisure eighty percent of the burden of
disease is from those communicable
causes diarrhea pneumonia and malaria
are particularly important in India a
country in real transition about 45% is
now non communicable disease forty five
percent is the communicable diseases and
the rest is injuries in China in 2010 it
looks much more like the US where 80
percent of the burden of disease is now
from heart disease cancer mental
disorders other non communicable causes
but China has lessons to tell the rest
of the developing world because if you
go back to 1990 25 percent of the burden
of disease in China was from
communicable diseases they've been
incredibly effective at tackling these
causes particularly in children over the
last two decades now if we go back to
2010 in China and see that
epidemiological shift
in that country we can also drill down
and show you the specific causes because
of course health policy interventions
clinical action requires specific
disease information and so each of those
boxes can be broken down into the 291
diseases and the thousand plus outcomes
but there's another way to see this
information I'll keep on the theme of
China and this is a ranked list
people love ranked lists you know
they're always in newspapers and so
we've made a ranked list on the left is
the ranked order of whatever outcome you
care about in this case overall health
loss in 1990 and on the right is the
ranked list for 2010 and the causes are
connected Reds or communicable causes
blues or NCDs greens or injuries key
story here is the big drops tuberculosis
diarrhea pneumonia going down 80 percent
in two decades in China and at the same
time ischemic heart disease going up by
almost 50% China has lessons to teach
the developing world China has lessons
to learn about how to manage ischemic
heart disease from places like the US
where we've brought ischemic heart
disease down over time
now disease and injury is not the whole
story because health is a got some
underlying determinants we think of them
as risk factors things that you can
modify in your own life but we can also
think about modifying at the community
level so the way to see that I'm going
to show you the view in this tool for
the u.s. is what are the leading risk
factors and in this case the number one
risk factor in the u.s. more than 14
almost 14 percent of all health loss all
years lost is diet
followed by smoking followed by obesity
and overweight followed by high blood
pressure high blood sugar physical
inactivity and alcohol the big dominant
risks in the u.s. now there's a billion
results and we could spend the rest of
today and tomorrow and the rest of the
week playing with these tools and I hope
you do but what I want to do is tell you
where this come from and what's the sort
of central motivation behind it and so
the story behind this tool starts
actually 40 years ago it starts with my
parents
deciding to drag our family from
suburban Minnesota by to Land Rover's in
the UK drive across the Sahara and start
and run a family as a hospital and so we
all had jobs my father was a physician
and I was the scrawny little kid here
and my job was to set up the hospital
pharmacy and run it and in that
experience the ten-year-old and in
subsequent places working for my parents
in Africa I ended up with two questions
that I'm still working on why are people
so sick in some communities and what
makes them so sick and how can we go
beyond giving care to individuals to
transforming the health of whole
populations now when I finish college
I got to start to address these
questions head-on and there were two
sources back in the late 80s early 90s
one source was the media where you were
simply inundated with a cacophony of the
number one problem is this that or
something else no way to get the big
picture the other source was to go at
the time to public health authorities
and I did I went and added up all the
claims about what people died from and
it turned out that everybody in the
world died three times over and I knew
one thing was true that you can only die
once now what that spawned is almost two
and a half decades of an effort to get
the four things together for us to
really understand patterns of health
around the world one is data data comes
in lots of forms we think about
digitized data these days but there's
lots of data that looks like this
that's handwritten down but the thing
about figuring this out for patterns of
health getting sort of real-time
information on health over time is it's
not like stock market prices where you
just grab the price and deliver it to a
laptop through some clever bit of
technology there's actually an
incredible bit of science behind
figuring out all the biases that are in
the data all the different case
definitions different countries use the
variation across places
in how doctors assigned causes of death
or make diagnoses so there's science
there's data and there's also the
evolution of a new cohort of data
scientists here's some of ours with
seeming superpowers at the Institute in
Seattle but it's the idea that we have a
new generation of people who have the
skills to take raw data about health and
turn it into information and the final
transformation in developing this type
of tool for everybody to use has been
the recognition of the power of
visualization here's a storyboarding
that we did for one of the first
visualizations namely how do you take
such rich information and make it
available to everyone why is this so
important why am I so passionate about
figuring out the answers to my two
questions I think one way to see that is
to look here in the US so on the top is
life expectancy by county this for women
it ranges from the counties in red to
the counties in green by 12 years huge
variation within the US and in fact in
this little tool on our website you can
ask the question what counties have a
life expectancy like which country in
the world so I'm going to highlight
Libya and those are counties in the US
where women's life expectancy is the
same as in Libya today now the reason
this is so important is that if we can
understand what are the diseases and
injuries and the risk factors that
explain patterns of health in each place
and we can learn from different
community communities there's a huge
potential to leapfrog and actually
transform health of different
populations so I want to leave you just
with three thoughts first this tool
allows us to ask questions that we
didn't even know to ask before some of
the Geographic patterns leap out at you
new hypotheses second we can learn from
success and failure all over the world
there's lessons China can teach lessons
China can learn lessons
and third the one that we're most
excited about is the power to engage
everyone in seeking understanding about
how to improve people's health because
this is no longer the purview of the
specialists this is in your hands thank
you very much
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